Enrichment waterfall
Also called: waterfall enrichment
An enrichment waterfall runs multiple data providers in sequence against a contact record, falling through to the next provider only when the one before it comes up empty, instead of trusting a single vendor to have every field.
No single data provider covers every field for every contact. Some are strong on verified work emails, some on mobile numbers, some on firmographic depth, and all of them have coverage gaps that show up exactly where a team needs the data most. A waterfall orders providers by expected accuracy and runs them in sequence: the most reliable source goes first, and only the records it misses fall through to the next one, then the next.
Clay is the tool most teams use to run this logic, chaining providers like FullEnrich, Prospeo, and LeadMagic behind one enrichment step instead of picking a single vendor and hoping. Vendor count isn't the point. A waterfall built from the right dozen or so providers, sequenced for a specific persona and geography, will outproduce a hundred-provider waterfall aimed at the wrong ICP. Past a certain point, adding a fortieth or eightieth provider mostly returns records the first ten already found, pulled from a different vendor's index of the same public web.
Cost per verified contact, not cost per credit
The number that actually matters isn't what a single credit costs. It's what a usable, deliverable contact costs once every dead end along the way gets paid for too. A cheap credit on a provider with a low find rate for a given ICP can end up costing more per verified contact than an expensive credit on a provider that's unusually good at finding that kind of person.
Waterfall orchestration is closer to standard practice than a niche technique at this point. OneGTM's 2026 State of GTM Engineering report, a self-selected survey of 228 GTM engineers across 30-plus countries that its own authors call meaningful but not statistically representative, found 84% report using Clay for exactly this kind of work, climbing to 96% among agencies specifically.
In practice
Most teams start narrow: a couple of providers matched to the exact persona and geography they're chasing, then add a new source only when there's a specific gap the existing sequence keeps missing. Run three sources through a workflow like Clay and every field can get tagged with which provider filled it and when, which matters the day a record looks wrong and someone needs to trace it back instead of just re-buying the row.
What people get wrong
The common mistake is treating vendor count as a proxy for quality, assuming a platform with 150 or 200 data sources must outperform one with 15. It doesn't work that way. Consumer data brokers, B2B contact databases, and social-scraped sources all draw from overlapping pools, so stacking a sixth or seventh provider onto five similar ones mostly returns records the first five already found. The redundancy costs money without adding coverage.
